CAREER: Spatial Modeling and Computation of Cell Signaling in Cell-to-Cell Communication

细胞间的通讯是细胞和系统功能的基础。细胞间的正常通讯依赖于细胞外和细胞内信号的精确控制和协调，以及诱导的细胞反应，如细胞形态发生。本项目将利用数学模型研究酵母交配系统的细胞间通讯，并将与实验人员密切合作进行。该项目将开发多细胞环境的模型和计算框架，包括复杂的细胞外和细胞内信号网络以及细胞形态变化。数值方法将被开发以满足计算建模的挑战。细胞通过感知和做出反应，如细胞运动和细胞形状变化，与环境或其他细胞相互作用。这些过程需要复杂的细胞网络和由此产生的反应的精确协调。这个项目将使用数学建模和计算来检查细胞和底层网络之间的相互作用。本研究中开发的模型和计算框架可以应用于其他系统，例如神经系统和免疫系统，其中细胞间通信是其功能的核心。因此，这个项目可以帮助医学研究。该项目的研究将与计算和数学方法的教育活动相结合，目的是培养本科生和研究生进行数学生物学的跨学科研究。

Cell-to-cell communication is fundamental to cell and system functions. Proper communication between cells relies upon precise control and coordination of extracellular and intracellular signaling, as well as the induced cellular responses such as cell morphogenesis. This project is to study cell-to-cell communication through yeast mating system using mathematical modeling and will be conducted in close collaboration with experimentalists. The project will develop the models and the computational framework for a multi-cell environment that includes complex extracellular and intracellular signaling networks and the cell morphological changes. Numerical methods will be developed to meet the computational modeling challenges. Cells interact with their environment or with other cells through sensing and making responses such as cell movement and cell shape change. These processes require precise coordination of intricate cellular networks and the resulting responses. This project will use mathematical modeling and computation to examine the interaction between cells and the underlying networks. The models and computational framework developed in this research can be applied to other systems, such as neural and immune systems, in which cell-to-cell communication is central to their function. Therefore, this project can aid medical research. The research in this project will be integrated with educational activities in computational and mathematical methods, with the aim of training undergraduate and graduate students for interdisciplinary research in mathematical biology.